Bioinspired Optimization of Germination Nutrients Based on Lactuca sativa Seedling Root Traits as Influenced by Seed Stratification, Fortification and Light Spectrums

Ronnie S. Concepcion II, Elmer P. Dadios

Abstract


Ecophysiological stimulators directly affect root morphology, especially in the embryonic stage. To enhance crop germination, an understanding of the root traits under abiotic inducers is needed. In this study, the combined impacts of white and red-blue light spectrums, cold stratification, and seed fortification involving various concentrations of bioactive chemicals namely simple nutrient addition program solution, gibberellic acid, α-naphthaleneacetic acid with thiamine hydrochloride were evaluated on loose-leaf lettuce (Lactuca sativa var. Altima) seedling root architecture. The growth-promoting effects of these nutrients varied the growth rate and morphology of roots which are immediately shown during the radicle development. Integrated computer vision and computational intelligence were employed for phytomorphological signatures extraction of seedlings that were cultivated in a customized modulable spectrum experimental chamber (MSPEC). Root phenotype model was developed using graph-cut segmentation and region properties, and the ideal germination nutrient concentration was optimized using bioinspired models with firefly algorithm optimal result of 204.1 mg/L for nitrate, 238.15 mg/L for phosphate, and 158.08 mg/L for potassium. It was verified that lettuce seedlings can endure highly concentrated nutrients, however, it is more sensitive to phosphate as this macronutrient significantly promotes root growth with the increased whorl number on white light spectrum exposure with cold stratification.


Keywords


Bioinspired algorithm; Computer vision; Lettuce; Root architecture phenotyping; Seed fortification and stratification

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References


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DOI: http://doi.org/10.17503/agrivita.v43i1.2843

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